本文選題：碳纖維復合材料 + 超聲波檢測技術��； 參考：《浙江大學》2016年博士論文

【摘要】：碳纖維復合材料(Carbon Fibre Reinforced Plastics,簡稱CFRP)在航空航天、車輛制造、大型工程建設等領域有著廣泛應用。在制造和使用過程中,CFRP內(nèi)部難免會出現(xiàn)缺陷,超聲檢測技術則是CFRP缺陷無損檢測的主要手段之一。隨著CFRP制造技術的進步,含有厚截面和曲面變厚度等區(qū)域的CFRP構(gòu)件已經(jīng)逐漸得到使用,這使得傳統(tǒng)的復合材料超聲檢測手段及信號處理技術已很難再滿足這些構(gòu)件中某些部分的檢測精度要求。針對這些材料的檢測難點,本文以CFRP超聲檢測的相關基金項目為依托,對厚截面CFRP和曲面變厚度CFRP孔隙缺陷的超聲檢測技術進行研究,全文的研究工作及成果如下。(1)對各類CFRP孔隙超聲檢測方法進行分析,得到各方法的特點。同時采用金相實驗法對論文涉及的CFRP的孔隙進行觀察與分析,得到孔隙的形態(tài)與分布特征。根據(jù)上述分析結(jié)果提出了基于超聲背散射信號處理的厚截面CFRP和曲面變厚度CFRP孔隙檢測方法。(2)對聲波在層狀粘滯媒質(zhì)中的反射與透射進行推導,得到聲波反射系數(shù)分布函數(shù)頻域模型。采用該模型對多層CFRP聲波反射系數(shù)進行計算,得到超聲波在層狀CFRP中產(chǎn)生共振的條件及CFRP層數(shù)對共振的影響。進一步采用該頻域模型對含孔隙層狀CFRP聲波反射系數(shù)進行計算,得到孔隙含量和分布對超聲波共振的影響。同時,還對層狀CFRP超聲脈沖反射信號各成分特征進行分析,在此基礎上建立了超聲檢測信號的時域及頻域模型。(3)提出了基于超聲背散射信號處理的厚截面CFRP局部集中孔隙缺陷識別方法。根據(jù)超聲背散射信號特征將其劃分為近表面信號和遠表面信號。針對近表面信號提出了基于共振結(jié)構(gòu)噪聲特征與基于共振結(jié)構(gòu)噪聲去除這兩種處理方法。針對遠表面信號則主要提出了基于信號相關分析的小波變換模極大值去噪方法。采用上述方法對厚截面CFRP局部集中孔隙進行識別,通過破壞性金相實驗驗證了上述信號處理方法的可行性。(4)提出了基于超聲背散射信號提升小波分解處理的曲面變厚度CFRP孔隙缺陷識別方法。通過金相實驗測定了超聲檢測完畢的曲面變厚度CFRP試塊孔隙率,同時分析了超聲脈沖反射信號的特征。采用提升小波變換對超聲背散射信號進行分解并分析得到了原始信號與各分解信號的特征。進一步對原始信號與選出的分解信號的特征隨孔隙率的變化關系進行分析,結(jié)果表明最優(yōu)分解信號特征比原始信號特征能更好地表征材料孔隙率。(5)提出了基于背散射信號能量特征的厚截面CFRP超聲C掃描成像方法和基于背散射分解信號能量特征的曲面變厚度CFRP超聲C掃描成像方法。同時,在基于第(3)點研究的基礎上提出了厚截面CFRP超聲背散射信號特征三維成像技術,生成的三維圖像能夠直觀地對厚截面CFRP局部集中孔隙進行表征。
[Abstract]:Carbon Fibre Reinforced Plastics, (CFRP) is widely used in aerospace, vehicle manufacturing, large engineering construction and so on. In the process of manufacture and use, defects will inevitably appear in CFRP, and ultrasonic testing technology is one of the main methods for nondestructive testing of CFRP defects. With the development of CFRP manufacturing technology, CFRP components with thick cross-sections and curved surfaces with variable thickness have been gradually used. This makes it difficult for traditional ultrasonic testing methods and signal processing techniques of composite materials to meet the precision requirements of some parts of these components. In view of the difficulties of testing these materials, this paper studies the ultrasonic detection technology of thick section CFRP and curved surface variable thickness CFRP pore defect based on the related fund items of CFRP ultrasonic detection. The research work and results are as follows: 1) the ultrasonic testing methods of CFRP pore are analyzed, and the characteristics of each method are obtained. At the same time, the porosity of CFRP was observed and analyzed by metallographic experiment, and the pore morphology and distribution characteristics were obtained. Based on the above analysis results, a method of detecting thick section CFRP and curved surface variable thickness CFRP pore based on ultrasonic backscattering signal processing is proposed to deduce the reflection and transmission of acoustic waves in layered viscous media. The frequency domain model of acoustic reflection coefficient distribution function is obtained. By using this model, the reflection coefficients of multilayer CFRP sound waves are calculated, and the conditions of ultrasonic resonance in layered CFRP and the influence of the number of CFRP layers on the resonance are obtained. Furthermore, the frequency domain model is used to calculate the acoustic reflection coefficient of layered CFRP with pores, and the effects of pore content and distribution on ultrasonic resonance are obtained. At the same time, the characteristics of each component of the layered CFRP ultrasonic pulse reflection signal are analyzed. On this basis, the time-domain and frequency-domain models of ultrasonic detection signals are established. A method for identifying local concentrated pore defects in thick cross-section CFRP based on ultrasonic backscattering signal processing is proposed. According to the characteristics of ultrasonic backscattering signal, it is divided into near surface signal and far surface signal. In this paper, two processing methods for near-surface signals are proposed, which are based on resonance structural noise characteristics and resonance structural noise removal. For the far surface signal, a wavelet transform modulus maximum denoising method based on signal correlation analysis is proposed. The method is used to identify the local concentrated pores in thick section CFRP. The feasibility of the above signal processing method is verified by destructive metallographic experiments. (4) A surface variable thickness CFRP pore defect identification method based on ultrasonic backscattering signal lifting wavelet decomposition is proposed. The porosity of the curved surface CFRP specimen with varying thickness was measured by metallographic experiments and the characteristics of ultrasonic pulse reflection signal were analyzed at the same time. The lifting wavelet transform is used to decompose the ultrasonic backscattering signal and the characteristics of the original signal and the decomposed signal are obtained. Further, the relationship between the characteristics of the original signal and the selected decomposition signal with porosity is analyzed. The results show that the optimal decomposed signal feature can better characterize the material porosity than the original signal feature.) A thick cross-section CFRP ultrasonic C-scan imaging method based on backscatter signal energy characteristics and a backscatter decomposition signal energy are proposed. The method of curved surface variable thickness CFRP ultrasonic C scan imaging is presented in this paper. At the same time, based on the research of the third point, a 3D imaging technique of thick cross-section CFRP ultrasonic backscattering signal is proposed. The generated 3D image can directly characterize the local concentrated pores of the thick cross-section CFRP.
【學位授予單位】：浙江大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：TB33;TN911.7

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